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  •   DSpace@Işık
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  • Mühendislik Fakültesi / Faculty of Engineering
  • Elektrik-Elektronik Mühendisliği Bölümü / Department of Electrical-Electronics Engineering
  • MF - Bildiri Koleksiyonu | Elektrik-Elektronik Mühendisliği Bölümü / Department of Electrical-Electronics Engineering
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Design of a third generation real-time cellular neural network emulator

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Date

2014

Author

Yıldız, Nerhun
Cesur, Evren
Tavşanoğlu, Ahmet Vedat

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Citation

Yıldız, N., Cesur, E. & Tavşanoğlu, A. V. (2014). Design of a third generation real-time cellular neural network emulator. Paper presented at the 2014 14th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA), 1-2. doi:10.1109/CNNA.2014.6888621

Abstract

In this paper, the features of the next generation Real-Time Cellular Neural Network Processor (RTCNNP-v3) are discussed. The RTCNNP-v2 structure is the only CNN implementation that is reported to be capable of processing full-HD 1080p@60 (1920 x 1080 resolution at 60 Hz frame rate) video images in real-time, due to its fully-pipelined architecture, however, it has some weaknesses like the inability to divide the processing in spatial domain, record and recall intermediate results to an external memory and has some issues in its internal memory coding. Those shortcomings are to be addressed in the next design of our CNN emulator - RTCNNP-v3, which will increase the range of applications and enable the implementation to match the requirements of the cutting-edge movie production technologies like UHD (4K) and the future FUHD (8K).

Source

2014 14th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA)

URI

https://hdl.handle.net/11729/1635
http://dx.doi.org/10.1109/CNNA.2014.6888621

Collections

  • MF - Bildiri Koleksiyonu | Elektrik-Elektronik Mühendisliği Bölümü / Department of Electrical-Electronics Engineering [211]
  • Scopus İndeksli Bildiri Koleksiyonu [414]
  • WoS İndeksli Bildiri Koleksiyonu [332]

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